📈 Matplotlib Practice – Visualizing Data from Basics to Real Use Cases

A complete hands-on journey through Matplotlib — from simple plots to real-world dataset visualizations.

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What’s Covered

In this I am going to cover all the basic concepts of Matplotlib

🧱 Core Visualizations

• Line Plot, Scatter Plot, Bar Chart
• Histogram, Pie Chart
• Customizing axes, labels, titles
• Multiple plots in a single figure
• Subplots, Layouts, Grids
• Styling: colors, markers, linewidths
• Saving figures

📊 Real-World Visualizations (Coming Soon)

• Data visualizations on 2 real-world datasets
• Use of Pandas + Matplotlib for insights
• Matplotlib + NumPy combo usage
• Preparing publication-ready charts

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📁 File Structure

matplotlib-practice/ ├── 01_line_scatter_bar.ipynb ├── 02_hist_pie_custom.ipynb ├── 03_layouts_subplots.ipynb ├── 04_styling_themes.ipynb ├── 05_advanced_tweaks.ipynb ← Coming Soon ├── 06_dataset1_visualization.ipynb ← Coming Soon ├── 07_dataset2_visualization.ipynb ← Coming Soon └── README.md

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🎯 Why This Exists

This repo is part of my personal journey in mastering Data Science and AI.
My goals:

• Understand Matplotlib thoroughly
• Create high-quality, customized charts
• Build visual storytelling skills using real data
• Share learning with others via clean notebooks

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🛠 Tech Used

• Python 3.x
• Matplotlib
• Jupyter Notebook
• (Pandas & NumPy for datasets)

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🚀 Getting Started

git clone https://github.com/piyushyadav0021/matplotlib-practice.git
cd matplotlib-practice